Meat tenderness describes primarily the force required to bite through a sample of meat, with more tender meat generally being more desirable. Tenderness factors strongly in determining overall palatability, and extensive tenderness research is ongoing worldwide (see for instance Hopkins D. L., and J. M. Thompson, 2002. Factors contributing to proteolysis and disruption of myofibrillar proteins and the impact on tenderization in beef and sheep meat. Australian Journal of Agricultural Research, 53, 149-166; Purchas, R. W., 1990. An assessment of the role of pH differences in determining the relative tenderness of meat from bulls and steers, Meat Science, 27, 129-140; Purchas, R. W., R. Aungsupakorn, 1993. Further investigations into the relationship between ultimate pH and tenderness for beef samples from bulls and steers, Meat Science, 34, 163-178; Watanabe, A., C. C. Daly and C. E. Devine, 1996. The effects of the ultimate pH of meat on tenderness changes during aging, Meat Science, 42(1), 67-78). So far non-invasive efforts to determine tenderness prior to consumption have met with limited success. Many official meat grading systems appraise visible parameters such as marbling as a predictor of tenderness, but they actually provide only a poor indication of tenderness. (Seideman, S. C., M. Koohmaraie, & J. D. Crouse, 1987. Factors associated with tenderness in young beef, Meat Science, 20(4), 281-291; Li, J., J. Tan, F. Martz, & H. Heimann, 1999. Image texture features as indicators for beef tenderness, Meat Science, 53, 17-22; Li, J., J. Tan, & P. Shatadal, 2001. Classification of tough and tender beef by image texture analysis, Meat Science, 57, 341-346).
An objective measure of tenderness is the shear force, determined with the Warner-Bratzler or the MIRINZ shear force devices under strict adherence to standardized procedures (Wheeler, T. L., Shackelford, S. D., Johnson, L. P., Miller, M. F., Miller, R. M. & Koohmaraie, M. 1997. A comparison of Warner Bratzler shear force assessment within and among institutions. J. Animal Science, 75, 2423-2432). Following guidelines the shear force can be determined accurately (Bekhit, A. E. D., Devine, C. E., Morton, J. D., Bickerstaffe, R., 2003. Towards unifying meat shear force measurement systems to determine meat tenderness. Proc. 49th Int. Congress of Meat Science & Technology, Buenos Aires, Brazil), but strong within-muscle variations exist that are poorly explained (Alsmeyer, R. L., J. W. Thornton and R. L. Hiner, 1965. Some dorsal-lateral location tenderness differences in the longissimus dorsi muscle of beef and pork. J. Animal Science 24, 526-530; Gariépy, C., S. D. M. Jones and W. M. Robertson, 1990. Variation in meat quality at three sites along the length of the beef longissimus muscle. Canadian Journal of Animal Science, 70, 707-710). Thus, unless a representative average is presented the shear force should be cautiously compared with other methods. A method that provides an overall or average tenderness value is also more useful for the consumer.
Shear force is the force required to cut through a sample of meat. The force applied to the meat varies as the blade cuts through the sample. First there will be an elastic deformation of the meat until the blade severs the tissue. The force applied until the blade actually shears the meat sample is the initial yield. The blade will then be required to apply a varying force to move through the meat sample at a constant speed. The maximum force required for cutting the meat sample is the peak force. The mean shear force is the average over all encountered forces applied while cutting the meat sample.
Imaging offers the most promising way to replace human visual assessment and random laboratory testing. Some researchers used visible light: for example Li et al. (1999); Li et al. (2001) (full references above); and Tan(Tan, J., 2004. Meat quality evaluation by computer vision, J. Food Eng., 61, 27-35), where in the latter a correlation between muscle texture and peak shear force has been reported, however the correlation was weak at R2=0.34. Near infrared spectroscopy has been used with some success. For example, see McGlone, V. A., Devine, C. E., Wells, R. W., 2005. Detection of tenderness, post rigor age and water status changes in sheep using near infrared spectroscopy, J. Near Infrared Spectroscopy, 13, 277-285; Devine, C. E. and McGlone V. A. 1998. On-line assessment of meat tenderness. Proc. 44th Int. Congress of Meat Science and Technology, Barcelona, 958-959; Park, B., Y. R. Chen, W. R. Hruschka, S. D. Shackelford, M. Koohmaraie, 1998. Near-infrared reflectance analysis for predicting beef longissimus tenderness, J. Animal Science, 76, (8), 2115-2120; and Liu, Y., B. G. Lyon, W. R. Windham, C. E. Realini, T. D. Pringle and S. Duckett, 2003. Prediction of color, texture, and sensory characteristics of beef steaks by visible and near infrared reflectance spectroscopy. A feasibility study. Meat Science, 65, (3), 1107-1115. Better results were generally achieved when an approximate and arbitrary classification sufficed (i.e. tough, medium, and tender), rather than on the use of a precise scale.
Dual energy x-ray absorptiometry (DEXA) already has applications in the primary industry (C. Kröger, C. M. Bartle, J. G. West, 2004. Non-invasive measurements of wool and meat properties, Proc. 18th Int. NDT, Montreal, Canada; Bartle, C. M., C. Kroger, and J. G. West, 2004. New uses of x-ray transmission techniques in the animal-based industries. Rad. Phys. Chem., 71, 843-851). Based on a crude tenderness scale a correlation was found between tenderness and x-ray images (PCT International Patent Application No. PCT/NZ01/00108 which is incorporated herein by reference). In this approach, the pre-processed false colour x-ray images created in an airport security DEXA scanner were separated into their red, green, and blue layers and the intensity from each layer was correlated to assumed tenderness depending on the type of cut, where a tenderloin steak was considered most tender and rib eye steak less tender and so on. The investigation revealed a distinct correlation based on the arbitrary scale. There were a number of disadvantages with this technique however. Firstly, the method was based on images pre-processed using proprietary software. Secondly, false colours are based on composition of the object, and while composition may contribute to tenderness, it remains constant over time while tenderness varies (for example with aging of the meat). Thus, the earlier technique may fail for investigation of variation of tenderness over time.
In this specification where reference has been made to patent specifications, other external documents, or other sources of information, this is generally for the purpose of providing a context for discussing the features of the invention. Unless specifically stated otherwise, reference to such external documents is not to be construed as an admission that such documents, or such sources of information, in any jurisdiction, are prior art, or form part of the common general knowledge in the art.